[Solved] Examine this Spark Structured Streaming code snippet in a Kappa architecture:df = spark.readStream.format("kafka") .option("kafka.bootstrap.servers", "localhost:9092") .option("subscribe", "topic1") .... | Hadoop

Hadoop - Modern Data Architecture with Hadoop

Examine this Spark Structured Streaming code snippet in a Kappa architecture:

df = spark.readStream.format("kafka")
  .option("kafka.bootstrap.servers", "localhost:9092")
  .option("subscribe", "topic1")
  .load()

result = df.selectExpr("CAST(value AS STRING) as data")
  .writeStream.format("console")
  .start()

What is the main issue with this code?

AIncorrect Kafka bootstrap server address format

BMissing checkpoint location for fault tolerance

CUsing 'console' sink is not supported in Spark Structured Streaming

DNot specifying the schema for Kafka messages

Step-by-Step Solution

Solution:

Step 1: Review streaming write options
Fault-tolerant streaming requires checkpointing.
Step 2: Check code for checkpoint option
Code lacks '.option("checkpointLocation", "path")'.
Step 3: Understand consequences
Without checkpointing, job cannot recover from failures.
Final Answer:
Missing checkpoint location for fault tolerance -> Option B
Quick Check:
Checkpointing is mandatory for reliable streaming [OK]

Quick Trick: Always set checkpointLocation in streaming writes [OK]

Common Mistakes:

Assuming console sink needs no checkpoint
Ignoring fault tolerance in streaming jobs
Confusing bootstrap server syntax

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Examine this Spark Structured Streaming code snippet in a Kappa architecture:

Step 1: Review streaming write options

Step 2: Check code for checkpoint option

Step 3: Understand consequences

Final Answer:

Quick Check:

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